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The AAPG/Datapages Combined Publications Database

GCAGS Transactions

Abstract


Gulf Coast Association of Geological Societies Transactions
Vol. 49 (1999), Pages 54-61

Characterization and 3-D Modeling of Turbidite Reservoir: A Case Study in Miocene Slope Deposits, Main Pass Area, Offshore Gulf Coast of Mexico

Kexian Yang(1), Jeffrey M. Yarus(1), William P. Cantanese(2)

(1) Smedvig Technologies, Inc., Houston, TX

(2) Barrett Resources Corporation, Houston, TX

ABSTRACT

A case study of a detailed characterization and 3-D modeling of a turbidite reservoir has been completed. Well correlation and seismic attribute analysis revealed a clear three dimensional facies architecture of a turbidite deposit reservoir. The study shows that a turbidite lobe is developed along with multiple and relatively high density gravity flow events.

Reservoir property and heterogeneity are controlled by facies architecture in a predictable pattern. The turbidite lobe has a typical mounded shape with a fairly straight feeder channel. The main body of the lobe is composed of stacked lenticular sand bodies, each representing a single gravity flow event. Reservoir sand is cleaner and thicker at the center lobe, rapidly becoming finer grained, with increasing shale interbeds, and finally pinches out towards the edge. Inside the lenticular sandbodies, thin shale patches can serve as vertical barriers to fluid flow during production. Facies distributions together with the structural pattern control the hydrocarbon resource potential and production performance in this area. They also provide important information for further exploration and development.

A 3-D reservoir model is built using stochastic object based techniques. To preserve the observed facies architecture in the model, the General Marked Point Process algorithm is employed. Specific object shapes are designed in the computer program for different facies. Multiple stage facies modeling enables the preservation of different levels of reservoir heterogeneity. Major geological features are preserved in the model and can be incorporated in future flow simulations.


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